3D Map Computation from Historical Stereo Photographs of Florence

The analysis of early photographic sources is fundamental for documenting and understanding the evolution of a city so rich in history and art as Florence. Indeed, by the 1860s several photographers used to work in town, and their images (often obtained through stereoscopic set-ups) can help us to reconstruct Florence in 3D as it was by the time of the Italian unification. The first and most delicate part of such reconstruction process is the computation of disparity maps from the historical stereo pairs. This is a very challenging task for fully-automatic computer vision algorithms, since XIX century photographs are affected by several problems—ranging from superficial damages to asynchronous acquisition—that are usually absent in modern images. In this paper we describe a semi-automatic method that, through minimal user input, allows the creation of coherent and realistic 3D maps of florentine scenes.

[1]  Peter Meer,et al.  Edge Detection with Embedded Confidence , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Yasushi Makihara,et al.  Object recognition supported by user interaction for service robots , 2002, Object recognition supported by user interaction for service robots.

[3]  Richard Szeliski,et al.  A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms , 2001, International Journal of Computer Vision.

[4]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  D. Schneider,et al.  PHOTOGRAMMETRIC ANALYSIS OF HISTORICAL IMAGE REPOSITORIES FOR VIRTUAL RECONSTRUCTION IN THE FIELD OF DIGITAL HUMANITIES , 2017 .

[6]  Erik Reinhard,et al.  Color Transfer between Images , 2001, IEEE Computer Graphics and Applications.

[7]  Peter Meer,et al.  Synergism in low level vision , 2002, Object recognition supported by user interaction for service robots.

[8]  Bob Fisher,et al.  Virtual and Augmented Architecture (VAA’01) , 2001, Springer London.

[9]  Christian Bräuer-Burchardt,et al.  Image Rectification for Reconstruction of Destroyed Buildings Using Single Views , 2001 .

[10]  Gabriele Bitelli,et al.  Historical Photogrammetry and Terrestrial Laser Scanning for the 3d Virtual Reconstruction of Destroyed Structures: a Case Study in Italy , 2017 .

[11]  Richard Szeliski,et al.  Computer Vision - Algorithms and Applications , 2011, Texts in Computer Science.

[12]  Jaakko Astola,et al.  From Local Kernel to Nonlocal Multiple-Model Image Denoising , 2009, International Journal of Computer Vision.